Glossary
Key terms and definitions
Last updated March 28, 2026
Agentic Coding
Agentic coding is an AI approach where the AI agent autonomously plans, writes, and executes code changes across multiple files with minimal human intervention.
AI Code Completion
AI code completion is real-time code suggestion technology that predicts and suggests the next lines of code as a developer types.
CI/CD
CI/CD is Continuous Integration and Continuous Deployment — the automated process of building, testing, and deploying code changes.
Code Generation
Code generation is the process of AI creating new code from natural language descriptions, specifications, or examples.
Code Review
Code review is the process of examining code changes before they are merged, now increasingly assisted by AI.
IDE (Integrated Development Environment)
An IDE is a software application that provides comprehensive tools for software development including code editing, debugging, and build automation.
Infrastructure as Code
Infrastructure as Code manages cloud infrastructure through code files rather than manual configuration.
LLM (Large Language Model)
A Large Language Model is the AI technology that powers coding assistants by understanding and generating human language and code.
No-Code Development
No-code development is building software applications using visual tools and AI without writing traditional programming code.
Open-Source AI Models
Open-source AI models are freely available machine learning models that can be downloaded, modified, and self-hosted for AI coding.
Prompt Engineering for Code
Prompt engineering for code is the practice of crafting effective instructions to get the best code output from AI tools.
RAG (Retrieval-Augmented Generation)
RAG combines AI generation with information retrieval from specific data sources to provide accurate grounded responses.
Self-Healing Tests
Self-healing tests use AI to automatically fix broken test locators and selectors when the UI changes.
Static Analysis
Static analysis examines code without executing it to find bugs, security vulnerabilities, and code quality issues.
Vector Database
A vector database stores and searches high-dimensional embeddings for AI applications like semantic search and RAG.